New digital solution to reduce waste of fresh fruit and vegetables
Researchers are working on a new digital solution to track changes in the quality of fresh fruit and vegetables in real-time. This solution can reduce food waste by informing companies digitally about quality changes and potential later losses.
Fruit and vegetables often lose quality before they arrive at a plate. So instead, they may end up as food waste somewhere in the supply chain.
Part of the challenge is that retailers and consumers do not know how long they can store fresh fruit and vegetables due to variations in the supply chain conditions.
Researchers are currently trying to solve this problem with the help of a digital solution called a “digital twin.” A digital twin is a virtual representation of an object or system that spans its lifecycle. It is continuously updated with measured real-time data and uses advanced analytical tools to help determine the residual shelf life and support sale decision-making.
This may sound complicated, but the purpose is to make it much easier for companies to make informed decisions - in this case: decisions on sale period and price to reduce food waste in the supply chain.
Alexandru Luca from the Department of Food Science at Aarhus University is coordinator of the DigiFresh project, which is funded by the European Institute of Innovation and Technology (EIT Food):
- We have determined how the supply chain conditions affect product quality from the moment of harvest until it reach a specific step in the chain. We are using this knowledge to create a user-friendly software solution based on digital twins.
Delayed effects of storage create waste
Unfortunately, there is a delayed effect of the storage conditions on the quality of fresh fruit and vegetables, which creates food waste.
Fruit and vegetables often do not show an immediate response to inappropriate storage conditions, so you cannot know what they have experienced from looking at the products. Therefore, you need to monitor and report their journey carefully.
- Let us take the example of strawberries. If the fruit are transported optimally at 1 °C and under high relative humidity; they can be stored in the fridge at the consumer for 5-6 days. This is on the condition that the consumer buys them immediately after arrival at the supermarket, Alexandru Luca explains.
- However, if the transport cooling system is out of order or not adequately controlled, the strawberries might look good when they arrive at the retailer, but the consumer, who buys them, may only be able to store them for 1-2 days at home. If the fruit are not purchased immediately, they might turn directly into food waste at the retailer or soon after purchase. It is challenging to react in a timely way if the retailers and consumers do not receive information about non-optimal storage conditions during the supply chain and their effects on the residual shelf life.
Predicting product quality and residual shelf life need new tools
However, even if you monitor the storage conditions in the supply chain, which some companies already do by installing sensors in the trucks or on boxes with products, one must still be able to translate the data into residual shelf life and the number of days before spoilage. Without mathematical models, this is impossible; this challenge is precisely the problem that the researchers are trying to solve in the DigiFresh project.
- Supply chain companies using sensors only, use the data to check if the temperature has been too high or low somewhere in the supply chain to determine if the transportation companies have fulfilled their contracts. However, at this point, they cannot predict product quality and the residual shelf life based on the collected data, Alexandru Luca says.
Models for strawberries and romaine salad
Since July this year, researchers at Aarhus University have focused on the two most crucial quality detrimental parameters: temperature and relative humidity and they have gathered data from the supply chain of strawberries and romaine salad.
They have analyzed how temperature and relative humidity cause different types of spoilage (fungal and bacterial growth) which is the source of mold and rot, senescence (which makes green leaves turn yellow), and how weight loss and dehydration relate to a decrease in turgidity and texture. The weight of strawberries decreases, for instance, when they are stored at too low humidity without packaging – the berries dehydrate, and their surface loses its shine and freshness.
- We have stored the berries and salad at different temperatures and relative humidity levels, and we have obtained valuable data for our mathematical models. Moreover, we have made simulation tests with fluctuating temperature and humidity conditions during storage to validate our models, Alexandru Luca explains.
Software expected on the market next year
The mathematical models, which can determine the residual shelf life of strawberries and salad, are currently being developed into software that is expected on the market next year.
- We will be offering a simple technology, which only requires a company to place a sensor inside a box with strawberries or in a package with Romaine salad during transport from A to B. Then, the sensor is read whenever the product arrives at a destination, and data is automatically uploaded to the cloud. The company can choose to follow the change of a specific product attribute or the quality change in general. Everything will be shown on the digital twin, Alexandru Luca states.
Selected partners will test the digital twin for strawberry and Romaine salad in 2022. Once the twins are launched on the market, the researchers can see the full potential of a new digital solution in the fruit and vegetable sector and what benefits it can provide retailers and consumers in ensuring product quality and reducing food waste.
We strive to ensure that all our articles live up to the Danish universities' principles for good research communication (scroll down to find the English version on the web-site). Because of this the article will be supplemented with the following information:
The project is funded by EIT Food.
Department of Food Science, Aarhus University, Denmark. Provides data on postharvest quality changes and shelf life of perishable products to be used for modelling. Contact to the Danish supply chain.
Katholieke Universiteit Leuven, Belgium. Model development.
Xsense Ltd, Migdal Tefen, Israel. Sensor provider and software development of the digital twins. Exploitation partner in DigiFresh.
Alexandru Luca, Postdoc, Department of Food Science, Aarhus University. Mobile: +45 20647429 - firstname.lastname@example.org